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Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
ISSN : 25800760     EISSN : 25800760     DOI : https://doi.org/10.29207/resti.v2i3.606
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) menerima artikel ilmiah dengan lingkup penelitian pada: Rekayasa Perangkat Lunak Rekayasa Perangkat Keras Keamanan Informasi Rekayasa Sistem Sistem Pakar Sistem Penunjang Keputusan Data Mining Sistem Kecerdasan Buatan/Artificial Intelligent System Jaringan Komputer Teknik Komputer Pengolahan Citra Algoritma Genetik Sistem Informasi Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Topik kajian lainnya yang relevan
Articles 25 Documents
Search results for , issue "Vol 5 No 3 (2021): Juni 2021" : 25 Documents clear
Rancang Bangun Pengukur Suhu Tubuh Dengan Multi Sensor Untuk Mencegah Penyebaran Covid-19 Helmy Yudhistira Putra; Utomo Budiyanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.2931

Abstract

During the COVID-19 pandemic, the price of preventive equipment such as masks and hand sanitizers has increased significantly. Likewise, thermometers are experiencing an increase and scarcity, this tool is also sought after by many companies for screening employees and guests before entering the building to detect body temperatures that are suspected of being positive for COVID-19. The use of a thermometer operated by humans is very risky because dealing directly with people who could be ODP (People Under Monitoring/Suscpected ) or even positive for COVID-19, therefore we need tools for automatic body temperature screening and do not involve humans for the examination. This research uses the MLX-90614 body temperature sensor equipped with an ultrasonic support sensor to detect movement and measure the distance between the forehead and the temperature sensor so that the body heat measurement works optimally, and a 16x2 LCD to display the temperature measurement results. If the measured body temperature is more than 37.5 ° C degrees Celsius then the buzzer will turn on and the selenoid door lock will not open and will send a notification to the Telegram messaging application. The final result obtained is the formation of a prototype device for measuring body temperature automatically without the need to involve humans in measuring body temperature to control people who want to enter the building so as to reduce the risk of COVID-19 transmission
Klasifikasi Data Aktivitas Setelah Joging Menggunakan Fuzzy Logic M. Deta Gian Faiz; Andrian Rakhmatsyah; Yasirandi, Rahmat
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.2938

Abstract

One of the routine activities that cause a lot of body fluids is jogging. Research shows that excessive jogging can disrupt the balance of body fluids so that you tire quickly in the long run. As a result, the body releases too much fluid. This makes someone forget or underestimate the need for fluids in the body. In this study, a detection system for body temperature, ambient temperature and heart rate was built for the classification of dehydration in the body to maintain fluid stability in the body. The system is built using the Pulse Sensor, Mlx90614, OpenWeatherAPI and the Android Platform. This study uses the Mamdani Fuzzy Logic method to determine the classification of user dehydration. The results of the research analysis contained a calibration test of the MLX90614 sensor against the Thermogun with an Error Rate value of 2.01% and an RMSE value of 0.9. Testing the Pulse Sensor against the Oximeter produces an Error Rate value of 1.54% and an RMSE value of 0.7. There is a difference in the difference in Deffuzification values ​​due to differences in the fixed points for each library. Matlab fixed point with a value behind the three digit point, 16 digit Fuzzy Sci-kit and the Builded System using a 15 digit point value.
Support Vector Machine to Predict Electricity Consumption in the Energy Management Laboratory Zamhuri Fuadi, Azam; Irsyad Nashirul Haq; Edi Leksono
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.2947

Abstract

Predicted electricity consumption is needed to perform energy management. Electricity consumption prediction is also very important in the development of intelligent power grids and advanced electrification network information. we implement a Support Vector Machine (SVM) to predict electrical loads and results compared to measurable electrical loads. Laboratory electrical loads have their own characteristics when compared to residential, commercial, or industrial, we use electrical load data in energy management laboratories to be used to be predicted. C and Gamma as searchable parameters use GridSearchCV to get optimal SVM input parameters. Our prediction data is compared to measurement data and is searched for accuracy based on RMSE (Root Square Mean Error), MAE (Mean Absolute Error) and MSE (Mean Squared Error) values. Based on this we get the optimal parameter values C 1e6 and Gamma 2.97e-07, with the result RSME (Root Square Mean Error) ; 0.37, MAE (meaning absolute error); 0.21 and MSE (Mean Squared Error); 0.14.
Optimalisasi Penyaluran Bantuan Pemerintah Untuk UMKM Menggunakan Metode Fuzzy C-Means Anggara Cahya Putra; Dwi Hartomo, Kristoko
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.2980

Abstract

Indonesian MSMEs were very seriously affected by the Covid-19 pandemic, which caused the Indonesian economy has experienced deceleration. The Indonesian government has taken several steps to keep economic activity running, such as direct cash assistance for micro-scale businesses but is having problems in obtaining real data so that assistance is not on target, the clustering method using Fuzzy C-Means (FCM) is used for grouping MSME data. FCM allows the data to be a member of all clusters in which each cluster has a membership degree value of 0-1. The data used is from the website of the Sleman Regency Cooperatives and SME Service. FCM classifies MSME data based on the attributes of revenue, assets and number of workers. This research resulted in grouping MSME data into 3 priority levels for MSMEs in obtaining assistance, namely high priority, medium priority, and low priority. The results of this study show that the number of MSMEs with high priority is 23,023 MSMEs, medium priority is 9,774 MSMEs and low priority is 3,159 MSMEs. The validation test of the FCM method uses the Partition Coefficient Index (PCI) which has a value of 0.826 which means that value good because it is close to 1.
Model Paralelisasi Algoritma Genetika Terpandu pada Sistem Penjadwalan Kuliah Universitas dengan Alokasi Waktu Dinamis Fachrie, Muhammad; Anita Fira Waluyo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.2988

Abstract

One of the many techniques used to solve the University Course Timetable Problem (UCTP) is Genetic Algorithm (GA) which is a technique in the field of Evolutionary Computation. However, GA has high computational complexity due to the large number of evolutionary operators that must be performed during the evolutionary process, so it takes a long time to produce an optimal timetable. The computation time will also increase when the number of optimized variables is very large, such as in UCTP. Of course, this makes the application less reliable by users. Therefore, this article proposes a parallelization model for GA to reduce computation time in solving UCTP problems. The proposed AG is designed with a multithreading CPU scheme and implements a guided creep mutation mechanism and eliminates the recombination mechanism to reduce more computation time. The proposed system was tested and evaluated using two different UCTP datasets from the University of Technology Yogyakarta which contained 878 and 1140 lecture meetings in even and odd semesters. Unlike the previous ones, this study discusses UCTP with dynamic time slots where the duration of the lecture depends on the course credits. From the tests that have been done, it is found that the GA that was built is able to generate optimal course timetable without any clashes in a relatively fast time, that is less than 60 minutes for 1140 lecture meetings and less than 20 minutes for 878 lecture meetings. The use of the multithreading CPU model has succeeded in reducing computation time by 62% when compared to the conventional model which only uses one thread.
Kriptografi Audio MP3 Menggunakan RSA dan Transposisi Kolom Paramita, Cinantya; Usman Sudibyo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.2996

Abstract

Mp3 is one form of audio file extension that is widely used today. With a variety of uses in a variety of mp3 systems become one of the audio extensions that are commonly found in technology systems of the Internet of Things era. However, with the many uses of the .mp3 file extension, there is a new problem, namely the security of the data itself. From these problems, the author aims to examine the security of the mp3 file by designing cryptographic science-based applications. The cryptographic algorithm used in the application is a combination of the asymmetric RSA 2048 algorithm and symmetric columnic transpositions. RSA 2048 algorithm was chosen because it has a key length in accordance with NIST standards in securing data. By combining the two algorithms, the application system will have the ability to manage mp3 files and encrypt mp3 files with the results of data that cannot be played like mp3 files in general. This application system will be developed by prototype method which is the best method in developing a system with trial and error in algorithm development.
Adaptive Streaming Server dengan FFMPEG dan Golang Kristiadi, David; Marwiyati
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.2998

Abstract

Quality of experience (QoE) when accessing video streaming becomes a challenge in varieties of network bandwidth/speed. Adaptive streaming becomes an answer to gain good QoE. An architecture system of the adaptive streaming server with Dynamic Adaptive Streaming over HTTP (DASH) was proposed. The system was consists of two services e.g transcoding and streaming. Transcoding service encodes an audio file, multi-bitrates video files, and manifest.mpd files. Streaming service serves client streaming requests that appropriate to client network profiles. The system is built using the Golang programming environment and FFMPEG. Transcoding service has some execution mode (serial and concurrent) and passing mode (1 pass and 2 passes). The transcoding service test results show that concurrent execution is faster 11,5% than the serial execution and transcoding using 1 pass is faster 46,95% than 2 passes but the bitrate of output video lower than the determinate bitrate parameter. The streaming service has a good QoE. In the 5 scenarios, buffer level=0 happens 5 times, and its total duration is 64 seconds. Buffer level=0 happens when extreme changes happen in network speed from fast to too slow.
Perbandingan Metode KNN Dan LBPH Pada Klasifikasi Daun Herbal Isman; Andani Ahmad; Abdul Latief
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.3006

Abstract

Herbal plants are plants that can be used as alternatives in natural healing of diseases, parts of plants that can be used such as roots, stems, tubers and leaves, in Southeast Sulawesi there are currently 1000 herbal plants and 10 sub-ethnicities that have been inventoried, according to research conducted by the Ministry of Health (Kemenkes). Indonesia has 6,000 - 7,000 medicinal plants, Southeast Sulawesi Province has a variety of herbal plants that are not found in other areas, such as Komba - Komba or Balakacida (Chromolaena Odorata). However, in the present era, the number of herbal plants is not accompanied by the knowledge of the community about the herbal plants themselves. The purpose of this study is to classify herbal plants and to compare the performance results of the K-Nearest Neighbor Method and Local Binary Pattern Histogram. From the test results of five types of herbal leaves in Southeast Sulawesi with a total of 100 data sets, the accuracy value for the K-Nearest Neighbor (KNN) method is obtained total accuracy value is 97,5%, while for the Local Binary Pattern Histogram (LBPH) method the total value is 94% of total accuracy value.
Analisis Perbandingan Algoritma Klasifikasi MLP dan CNN pada Dataset American Sign Language Naufal, Mohammad Farid; Sesilia Shania; Jessica Millenia; Stefan Axel; Juan Timothy Soebroto; Rizka Febrina P.; Mirella Mercifia
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.3009

Abstract

People who have hearing loss (deafness) or speech impairment (hearing impairment) usually use sign language to communicate. One of the most basic and flexible sign languages ​​is the Alphabet Sign Language to spell out the words you want to pronounce. Sign language uses hand, finger, and face movements to speak the user's thoughts. However, for alphabetical sign language, facial expressions are not used but only gestures or symbols formed using fingers and hands. In fact, there are still many people who don't understand the meaning of sign language. The use of image classification can help people more easily learn and translate sign language. Image classification accuracy is the main problem in this case. This research conducted a comparison of image classification algorithms, namely Convolutional Neural Network (CNN) and Multilayer Perceptron (MLP) to recognize American Sign Language (ASL) except the letters "J" and "Z" because movement is required for both. This is done to see the effect of the convolution and pooling stages on CNN on the resulting accuracy value and F1 Score in the ASL dataset. Based on the comparison, the use of CNN which begins with Gaussian Low Pass Filtering preprocessing gets the best accuracy of 96.93% and F1 Score 96.97%
Sistem Pemantau Kondisi Lingkungan Pertanian Tanaman Pangan dengan NodeMCU ESP8266 dan Raspberry Pi Berbasis IoT Ambarwari, Agus; Dewi Kania Widyawati; Anung Wahyudi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i3.3037

Abstract

The increasing need for food is not in line with the clearing of agricultural land for food crops. So that the effort to increase the productivity of agricultural products is by applying precision agriculture. However, in reality, precision agriculture is difficult to apply to conventional processes, where farmers come to the farm, collect data, then carry out maintenance. This method will make production results not optimal because maintenance is not done accurately. This study introduces a monitoring system for environmental conditions based on the Internet of Things (IoT) for agricultural land, where trials are carried out in a greenhouse. The system that has been developed consists of several sensors designed to collect information related to agricultural environmental conditions, including DHT22 sensor (temperature and humidity), DS18B20 sensor (soil temperature), soil moisture sensor (moisture content in the soil), and BH1750 sensor (light intensity). Based on the Message Queuing Telemetry Transport (MQTT) protocol, the data is sent to a gateway (Raspberry Pi) and a local server via a wireless network to be stored in a database. By using the Node-RED Dashboard, the received sensor data is then displayed on the browser every time the sensor sends data. In addition, the local server also publishes sensor data to the public MQTT broker so that sensor data can be accessed through the MQTT Dashboard application on a smartphone. The results of testing for 25 days of the system running obtained an average success of the system in storing data of 99.64%.

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